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MyOpenCV.cpp
资源名称：matcher.rar　[点击查看]
上传用户：quan1896
上传日期：2013-04-17
资源大小：94k
文件大小：9k
源码类别：

2D图形编程

开发平台：

Visual C++

MyOpenCV.cpp：源码内容
  1. // MyOpenCV.cpp : my opencv functions
  2. //
  3. /////////////////////////////////////////////////////////////////////////////
  4. #include "stdafx.h"
  6. #include "MyOpenCV.h"
  7. #include <math.h>
  9. // 画十字形标记函数
  10. void quPlotCross(CvArr* img,CvPoint pt,double color,int thickness,int radius)
  11. {
  12. CvPoint left,right,up,down;
  13. left.x=pt.x-radius;left.y=pt.y;
  14. right.x=pt.x+radius;right.y=pt.y;
  15. up.x=pt.x;up.y=pt.y+radius;
  16. down.x=pt.x;down.y=pt.y-radius;
  17. cvLine(img,left,right,color,thickness,0);
  18. cvLine(img,up,down,color,thickness,0);
  19. }
  21. // 特征点初始匹配函数
  22. void quCornermatcher(IplImage* grayImage1,IplImage* grayImage2,int patch_radius,int max_disparity,
  23.  CvPoint2D32f* corners1,CvPoint2D32f* corners2,int cornerCount,
  24.  CvPoint2D32f* matches1,CvPoint2D32f* matches2,int* nmatches,int* mat12,int* mat21)
  25. {
  26. int x1,y1,x2,y2;
  27. double norm,minnorm;
  28. IplImage* patchimg1=0;
  29. IplImage* patchimg2=0;
  30. *nmatches=0;
  32. patchimg1=cvCreateImage(cvSize(patch_radius*2+1,patch_radius*2+1),IPL_DEPTH_8U,1);
  33. patchimg2=cvCreateImage(cvSize(patch_radius*2+1,patch_radius*2+1),IPL_DEPTH_8U,1);
  35. iplSetBorderMode(grayImage1,IPL_BORDER_CONSTANT,IPL_SIDE_ALL,0);
  36. iplSetBorderMode(grayImage2,IPL_BORDER_CONSTANT,IPL_SIDE_ALL,0);
  38. //正向相关匹配(1->2)
  39. for(int i=0;i<cornerCount;i++)
  40. {
  41. minnorm=1.0e8;
  42. mat12[i]=-1;//if mat*[i]<0 canot found matches
  43. x1=cvRound(corners1[i].x);y1=cvRound(corners1[i].y);
  45. cvSetImageROI(grayImage1,cvRect(x1-patch_radius,y1-patch_radius,patch_radius*2+1,patch_radius*2+1));
  46. cvSetZero(patchimg1);
  47. iplCopy(grayImage1,patchimg1);
  48. cvSetImageROI(grayImage1,cvRect(0,0,grayImage1->width,grayImage1->height));
  50. for(int j=0;j<cornerCount;j++)
  51. {
  52. x2=cvRound(corners2[j].x);y2=cvRound(corners2[j].y);
  53. if((x1-x2)*(x1-x2)+(y1-y2)*(y1-y2)<max_disparity*max_disparity)
  54. {
  55. cvSetImageROI(grayImage2,cvRect(x2-patch_radius,y2-patch_radius,patch_radius*2+1,patch_radius*2+1));
  56. cvSetZero(patchimg2);
  57. iplCopy(grayImage2,patchimg2);
  58. cvSetImageROI(grayImage2,cvRect(0,0,grayImage2->width,grayImage2->height));
  60. norm=iplNorm(patchimg1,patchimg2,IPL_L2);//相关系数(图像2范数)
  62. if(norm<minnorm)
  63. {
  64. minnorm=norm;
  65. mat12[i]=j;
  66. }
  67. }
  68. }
  70. cvSetImageROI(grayImage1,cvRect(0,0,grayImage1->width,grayImage1->height));
  71. cvSetImageCOI(grayImage1,0);
  72. }
  74. //反向相关匹配(2->1)
  75. for(i=0;i<cornerCount;i++)
  76. {
  77. minnorm=1.0e8;
  78. mat21[i]=-1;//if mat*[i]<0 canot found matches
  79. x2=cvRound(corners2[i].x);y2=cvRound(corners2[i].y);
  81. cvSetImageROI(grayImage2,cvRect(x2-patch_radius,y2-patch_radius,patch_radius*2+1,patch_radius*2+1));
  82. cvSetZero(patchimg2);
  83. iplCopy(grayImage2,patchimg2);
  84. cvSetImageROI(grayImage2,cvRect(0,0,grayImage2->width,grayImage2->height));
  86. for(int j=0;j<cornerCount;j++)
  87. {
  88. x1=cvRound(corners1[j].x);y1=cvRound(corners1[j].y);
  89. if((x1-x2)*(x1-x2)+(y1-y2)*(y1-y2)<max_disparity*max_disparity)
  90. {
  91. cvSetImageROI(grayImage1,cvRect(x1-patch_radius,y1-patch_radius,patch_radius*2+1,patch_radius*2+1));
  92. cvSetZero(patchimg1);
  93. iplCopy(grayImage1,patchimg1);
  94. cvSetImageROI(grayImage1,cvRect(0,0,grayImage1->width,grayImage1->height));
  96. norm=iplNorm(patchimg1,patchimg2,IPL_L2);//相关系数(图像2范数)
  98. if(norm<minnorm)
  99. {
  100. minnorm=norm;
  101. mat21[i]=j;
  102. }
  103. }
  104. }
  106. cvSetImageROI(grayImage2,cvRect(0,0,grayImage2->width,grayImage2->height));
  107. cvSetImageCOI(grayImage2,0);
  108. }
  110. //重组匹配点矩阵
  111. for(i=0;i<cornerCount;i++)
  112. {
  113. //if(mat12[i]>=0)//(1->2)
  114. if(mat12[i]>=0&&mat21[mat12[i]]==i)//(1->2)&&(2->1)
  115. {
  116. matches1[*nmatches].x=corners1[i].x;matches1[*nmatches].y=corners1[i].y;
  117. matches2[*nmatches].x=corners2[mat12[i]].x;matches2[*nmatches].y=corners2[mat12[i]].y;
  118. (*nmatches)++;
  119. }
  120. }
  122. cvReleaseImage(&patchimg1);
  123. cvReleaseImage(&patchimg2);
  124. }
  126. // 基于F的引导匹配函数
  127. void quGuidematcher(IplImage* grayImage1,IplImage* grayImage2,int patch_radius,int max_disparity,double epidis,
  128.  CvPoint2D32f* corners1,CvPoint2D32f* corners2,int cornerCount,CvMat* fundMatr,
  129.  CvPoint2D32f* matches1,CvPoint2D32f* matches2,int* nmatches,int* mat12,int* mat21)
  130. {
  131. int x1,y1,x2,y2;
  132. double norm,minnorm;
  133. CvMat* points1=0;
  134.     CvMat* points2=0;
  135.     CvMat* wpoints1=0;
  136.     CvMat* wpoints2=0;
  137.     CvMat* corrLines1=0;
  138.     CvMat* corrLines2=0;
  139. IplImage* patchimg1=0;
  140. IplImage* patchimg2=0;
  141. *nmatches=0;
  143.     points1=cvCreateMat(2,cornerCount,CV_32F);
  144.     points2=cvCreateMat(2,cornerCount,CV_32F);
  145.     wpoints1=cvCreateMat(3,cornerCount,CV_64F);
  146.     wpoints2=cvCreateMat(3,cornerCount,CV_64F);
  147.     corrLines1=cvCreateMat(3,cornerCount,CV_64F);
  148.     corrLines2=cvCreateMat(3,cornerCount,CV_64F);
  150. for(int i=0;i<cornerCount;i++)
  151. {
  152. cvmSet(points1,0,i,corners1[i].x); cvmSet(points1,1,i,corners1[i].y);
  153. cvmSet(points2,0,i,corners2[i].x); cvmSet(points2,1,i,corners2[i].y);
  154. }
  155. cvMake3DPoints(points1,wpoints1);
  156.     cvMake3DPoints(points2,wpoints2);
  158. patchimg1=cvCreateImage(cvSize(patch_radius*2+1,patch_radius*2+1),IPL_DEPTH_8U,1);
  159. patchimg2=cvCreateImage(cvSize(patch_radius*2+1,patch_radius*2+1),IPL_DEPTH_8U,1);
  161. iplSetBorderMode(grayImage1,IPL_BORDER_CONSTANT,IPL_SIDE_ALL,0);
  162. iplSetBorderMode(grayImage2,IPL_BORDER_CONSTANT,IPL_SIDE_ALL,0);
  164. cvComputeCorrespondEpilines(wpoints1,1,fundMatr,corrLines2);
  165. cvComputeCorrespondEpilines(wpoints2,2,fundMatr,corrLines1);
  167. //正向引导匹配(1->2)
  168. for(i=0;i<cornerCount;i++)
  169. {
  170. minnorm=1.0e8;
  171. mat12[i]=-1;//if mat*[i]<0 canot found matches
  172. x1=cvRound(corners1[i].x);y1=cvRound(corners1[i].y);
  174. cvSetImageROI(grayImage1,cvRect(x1-patch_radius,y1-patch_radius,patch_radius*2+1,patch_radius*2+1));
  175. cvSetZero(patchimg1);
  176. iplCopy(grayImage1,patchimg1);
  177. cvSetImageROI(grayImage1,cvRect(0,0,grayImage1->width,grayImage1->height));
  179. CvMat pnt1,pnt2;
  180. CvMat lin1,lin2;
  181. cvGetCol(wpoints1,&pnt1,i);
  182. cvGetCol(corrLines2,&lin2,i);
  184. for(int j=0;j<cornerCount;j++)
  185. {
  186. x2=cvRound(corners2[j].x);y2=cvRound(corners2[j].y);
  188. if((x1-x2)*(x1-x2)+(y1-y2)*(y1-y2)<max_disparity*max_disparity)
  189. {
  190.                 cvGetCol(wpoints2,&pnt2,j);
  191.                 cvGetCol(corrLines1,&lin1,j);
  192.                 double dist1,dist2;
  193.                 dist1=fabs(cvDotProduct(&pnt1,&lin1));
  194.                 dist2=fabs(cvDotProduct(&pnt2,&lin2));
  196. if(dist1<epidis && dist2<epidis)
  197. {
  198. cvSetImageROI(grayImage2,cvRect(x2-patch_radius,y2-patch_radius,patch_radius*2+1,patch_radius*2+1));
  199. cvSetZero(patchimg2);
  200. iplCopy(grayImage2,patchimg2);
  201. cvSetImageROI(grayImage2,cvRect(0,0,grayImage2->width,grayImage2->height));
  203. norm=iplNorm(patchimg1,patchimg2,IPL_L2);//相关系数(图像2范数)
  205. if(norm<minnorm)
  206. {
  207. minnorm=norm;
  208. mat12[i]=j;
  209. }
  210. }
  211. }
  212. }
  214. cvSetImageROI(grayImage1,cvRect(0,0,grayImage1->width,grayImage1->height));
  215. cvSetImageCOI(grayImage1,0);
  216. }
  218. //反向引导匹配(2->1)
  219. for(i=0;i<cornerCount;i++)
  220. {
  221. minnorm=1.0e8;
  222. mat21[i]=-1;//if mat*[i]<0 canot found matches
  223. x2=cvRound(corners2[i].x);y2=cvRound(corners2[i].y);
  225. cvSetImageROI(grayImage2,cvRect(x2-patch_radius,y2-patch_radius,patch_radius*2+1,patch_radius*2+1));
  226. cvSetZero(patchimg2);
  227. iplCopy(grayImage2,patchimg2);
  228. cvSetImageROI(grayImage2,cvRect(0,0,grayImage2->width,grayImage2->height));
  230. CvMat pnt1,pnt2;
  231. CvMat lin1,lin2;
  232. cvGetCol(wpoints2,&pnt2,i);
  233. cvGetCol(corrLines1,&lin1,i);
  235. for(int j=0;j<cornerCount;j++)
  236. {
  237. x1=cvRound(corners1[j].x);y1=cvRound(corners1[j].y);
  238. if((x1-x2)*(x1-x2)+(y1-y2)*(y1-y2)<max_disparity*max_disparity)
  239. {
  240.                 cvGetCol(wpoints1,&pnt1,j);
  241.                 cvGetCol(corrLines2,&lin2,j);
  242.                 double dist1,dist2;
  243.                 dist1=fabs(cvDotProduct(&pnt1,&lin1));
  244.                 dist2=fabs(cvDotProduct(&pnt2,&lin2));
  246. if(dist1<epidis && dist2<epidis)
  247. {
  248. cvSetImageROI(grayImage1,cvRect(x1-patch_radius,y1-patch_radius,patch_radius*2+1,patch_radius*2+1));
  249. cvSetZero(patchimg1);
  250. iplCopy(grayImage1,patchimg1);
  251. cvSetImageROI(grayImage1,cvRect(0,0,grayImage1->width,grayImage1->height));
  253. norm=iplNorm(patchimg1,patchimg2,IPL_L2);//相关系数(图像2范数)
  255. if(norm<minnorm)
  256. {
  257. minnorm=norm;
  258. mat21[i]=j;
  259. }
  260. }
  261. }
  262. }
  264. cvSetImageROI(grayImage2,cvRect(0,0,grayImage2->width,grayImage2->height));
  265. cvSetImageCOI(grayImage2,0);
  266. }
  269. //重组匹配点矩阵
  270. for(i=0;i<cornerCount;i++)
  271. {
  272. if(mat12[i]>=0)//(1->2)
  273. if(mat12[i]>=0&&mat21[mat12[i]]==i)//(1->2)&&(2->1)
  274. {
  275. matches1[*nmatches].x=corners1[i].x;matches1[*nmatches].y=corners1[i].y;
  276. matches2[*nmatches].x=corners2[mat12[i]].x;matches2[*nmatches].y=corners2[mat12[i]].y;
  277. (*nmatches)++;
  278. }
  279. }
  281.     cvReleaseMat(&points1);
  282.     cvReleaseMat(&points2);
  283.     cvReleaseMat(&wpoints1);
  284.     cvReleaseMat(&wpoints2);
  285.     cvReleaseMat(&corrLines1);
  286.     cvReleaseMat(&corrLines2);
  287. cvReleaseImage(&patchimg1);
  288. cvReleaseImage(&patchimg2);
  289. }